Challenges in Atmospheric Science and Air Pollution: Directions and Questions for Modelers Sherri W. Hunt Office of Science Advisor, Policy, and Engagement Office of Research and Development 18 th Annual CMAS Conference, Chapel Hill, NC October 21-23, 2019 Office of Research and Development
Disclaimer: The views expressed in this presentation are those of the authors and do not necessarily reflect the views or policies of the U.S. EPA. Office of Research and Development Office of Research and Development 2 National Exposure Research Laboratory , Computational Exposure Division
Why do we have air quality models? • To better understand air quality • To identify sources of pollution • To develop strategies to reduce exposure to harmful pollutants • To inform policy and develop plans for compliance 3
A Little History Before we had computer models, we had our senses. 4
Daytime London, 1952 Bell and Davis, EHP, 2001 • Total Suspended Material reached 1500 µ g/m 3 • 12,000 Excess Deaths Attributed to Event Photos: Erwin Hampe 5
Geneva Steel, Utah Valley, 1989 (PM 10 = 150 m g/m 3 ) 6
Utah Valley, 1989, (PM10 = 220 m g/m 3 ) There are 250,000+ people breathing down there — including asthmatic children and elderly with CV and COPD. Does this pollution affect their health? 7
Very Simple Air Quality Model or Steel Mill Closed Steel Mill Open 8
When the steel mill was open, total children’s hospital admissions for respiratory conditions approx. doubled. 300 Mill Open 250 m g/m 3 /Numbers of Admissions Total Mean High 200 PM 10 levels for Bronchitis Months and Included Asthma 150 Pneumonia and Pleurisy Mill Mean PM 10 Arden Pope levels for Closed 100 Months Included 50 m 0 Children's respiratory hospital admissions PM 10 concentrations 9 Sources: Pope. Am J Pub Health.1989; Pope. Arch Environ Health. 1991
Early Air Quality Model The first urban air quality model with spatial and temporal resolution was developed for the Los Angeles basin in California, USA Development of Atomic Models S. Reynolds, P. Roth, J. Seinfeld, Mathematical modeling of 10 photochemical air Pollution, Atmos. Environ., 7 (1973), pp. 1033-1061
Many, Many Model Improvements • Finer scale resolution • More complete chemical mechanism • Inclusion of aerosols • Clouds and radiation • Linking global and regional models for better treatment of long range transport and climate impacts • More complex land/atmosphere interactions • Updates to emissions inventories • Data fusion for meteorology and measurements from the ground or above • and more… 11
Current Air Quality Model Many many hard working EPA scientists 12
But Models Still Have Limitations • For example, O 3 bias persists and varies with season • When O 3 concentration matches measurements, we lack information to assess whether it’s correct for the right reasons 13 Appel, K. W., et al., Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1, Geoscientific Model Development 10, 1703-1732, doi:10.5194/gmd-10-1703-2017 (2017).
Why do we have air quality models? • To better understand air quality • To identify sources of pollution • To develop strategies to reduce exposure to harmful pollutants • To inform policy and develop plans for compliance 14
Cleaner Air Leads to New Questions Declining National Air Pollutant Concentration Averages • Decreased emissions from many large regional sources means other sources are now important • Long-range transport and background may be increasing in importance • Improvements in air quality are not uniform • Lower concentrations require different models 15 https://gispub.epa.gov/air/trendsreport/2019/#home
How Do We Improve AQ Models? • Adding heterogenous chemistry • Improving chemical mechanism • Including phase state of aerosols • Improvements to emissions inventories • Using more observations for data assimilation and evaluation • Adding dynamic boundary conditions • Improving representation of physics and dynamics (boundary layer schemes, convection,…) • …. Build a Better Model Infrastructure 16
EPA’s Modeling Efforts • EPA’s focus is to protect human health and the environment • Allows global-to-local environmental influences to be holistically considered within same modeling system • Combines a version of Model for Prediction Across Scales (MPAS) with components of Community Multiscale Air Quality (CMAQ) model • EPA-funded Air Climate and Energy Centers are developing reduced form models and considering potential changes in energy production • New STAR grants will support projects on Chemical Mechanisms To Address New Challenges In Air Quality Modeling 17
NOAA’s Modeling Efforts • NOAA’s focus is on weather and air quality forecasting • The Earth Prediction Innovation Center (EPIC) will accelerate community-developed scientific and technological advancements into the operational applications for Numerical Weather Prediction (NWP) by supporting a Unified Forecast System (UFS) community model. • NOAA works closely with entities in the weather enterprise (public, private, and academic) to inform the planning, development, and strategy for EPIC. 18
NASA’s Modeling Efforts • NASA’s focus is on a more complete understanding of the earth’s atmosphere and ways to understand and use satellite data • Support model development for air quality forecasting and applications 19
NSF’s Modeling Efforts Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA) • NSF’s focus is fundamental science System for Integrated Modeling of the Atmosphere (SIMA) Land research Ocean Model Atmosphere Model Model • (global, regional, LES, box,…) NCAR is a focal point for research in the field of atmospheric Common Physics Framework Coupler Sea Ice sciences Model Chem. Solver Unified Photolysis Aerosols Etc. physics Land Ice MICM suite Emissions Model 20 Atmospheric Chemistry Observations and Modeling Laboratory
European Modeling Efforts Atmosphere Monitoring C o p e r n i c u s A t m o s p h e r e M o n i t o r i n g S e r v i c e ECMWF manages the Copernicus Atmosphere Monitoring Service ( CAMS ), one of 6 thematic Services of the EU Space flagship programme Copernicus 12 years of continuous daily global CAMS regional forecasts seen in the atmospheric composition forecasts Windy app and website 21
How Do We Improve AQ Models? • Many big modeling activities currently (and previously) • We need to leverage resources across organizations • We don’t need one single modeling system • We do need interoperability across modeling systems so new knowledge can be shared Sherri’s Thoughts: We have to work together – really 22
Why do we have air quality models? • To better understand air quality • To identify sources of pollution • To develop strategies to reduce exposure to harmful pollutants • To inform policy and develop plans for compliance 23
A Little Bit of Epidemiology • Epidemiology examines relationships between Time Series Study exposure and health effects (e.g., heart/lung function, hospital admissions, mortality) • AQ models can improve exposure estimates • Kinds of observational epidemiology studies: • Short-term exposure: time-series, case-crossover, panel studies • Long-term exposure: cohort studies less healthy Cohort Study Panel Study more healthy less dead exposed exposed alive more exposed 24
What About Spatial Resolution? Resolution = 10 km Resolution = 1 km • Finer resolution does not mean better exposure information • Most people don’t stay within 1 km (except elderly) • For population level studies (e.g. time-series), health data is often only available at the county or census track level CO 2 emissions inventory 25 McDonald et al. ( J. Geophys. Res. 2014)
Model-Data Fusion Is Useful • A major advancement in the Draft PM Integrated Science Assessment (ISA) is the inclusion of model-data fusion methods to estimate exposure in epidemiologic studies • Helpful for estimating exposure in places without monitors, especially rural areas • Evaluation is challenging, because these models fit their datasets to the network measurements and then make predictions in places and at scales that are poorly sampled by the network (e.g. rural areas or 1-km scale) Sherri’s Thoughts: Model-data fusion is useful but still needs evaluation 26 Finer resolution might not provide an improved exposure estimate
Health Effects and PM Components National Particle Component Toxicity Initiative • The NPACT studies are the most systematic effort to combine epidemiologic and toxicologic analyses of the health effects of PM components to date • The studies found associations between health effects and sulfate particles (primarily from coal combustion) and, to a somewhat lesser extent, traffic sources … but the NPACT Panel concluded that the studies do not provide compelling evidence that any specific source, component, or size class of PM may be excluded as a possible contributor to PM toxicity. 27
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